Junior Backend Engineer - AI/ML Platform

As a Junior Backend Engineer at our early-stage startup in Mumbai, you will play a crucial role in ensuring the smooth operation of our Predictive Marketing Engine. If you have a passion for backend development and a strong understanding of AI and ML ecosystems, this opportunity is tailored for you. Key Responsibilities: - Data Pipeline Ownership: Maintain and optimize robust ETL pipelines pulling live data from endpoints into our staging databases. - ML Deployment (MLOps Support): Assist in containerizing existing PyTorch models, transformers, and LLM scripts using Docker, and deploy them under guidance. - Code Quality: Refactor existing MVP research code into clean, modular, production-ready Python following team standards. - API Development: Write and optimize backend endpoints using FastAPI/Flask to seamlessly serve ML model inferences to our frontend client. - CI/CD & Monitoring: Manage Git workflows, maintain environment consistency, and monitor live model performance, API latencies, and logs. Qualification Required: - Experience: 2 years of professional software engineering experience, focused on backend development or data engineering. - Core Stack: Strong proficiency in Python and web framework development (FastAPI/Flask preferred). - Containerization: Practical, hands-on experience writing Dockerfiles and managing containerized applications. - Databases: Solid understanding of SQL (PostgreSQL) and NoSQL (MongoDB) for managing unstructured text data and user state. - AI/ML Familiarity: Basic experience interacting with PyTorch, Hugging Face pipelines, or commercial LLM APIs (OpenAI/Gemini). Understanding of passing data through an API to a model. Bonus Points (Nice-to-Haves): - Experience with frontend frameworks (React/Next.js) or building quick internal tools using Streamlit. - Basic knowledge of Agentic AI or Multi-Agent workflows (LangChain, LlamaIndex, AutoGen). - Familiarity with AdTech APIs (Google Ads, Meta Ads). If you join us, you will benefit from direct mentorship, hands-on exposure to PyTorch, LLMs, MLOps, and cloud infrastructure, and a clear path to a full-time role. In our startup environment, your work ships fast and makes an immediate impact. If you are ready to thrive in a fast-paced startup environment and contribute to building a deep-tech architecture from the ground up, please send your resume, salary expectations, references, and GitHub/LinkedIn/portfolio/personal website to the provided email address. As a Junior Backend Engineer at our early-stage startup in Mumbai, you will play a crucial role in ensuring the smooth operation of our Predictive Marketing Engine. If you have a passion for backend development and a strong understanding of AI and ML ecosystems, this opportunity is tailored for you. Key Responsibilities: - Data Pipeline Ownership: Maintain and optimize robust ETL pipelines pulling live data from endpoints into our staging databases. - ML Deployment (MLOps Support): Assist in containerizing existing PyTorch models, transformers, and LLM scripts using Docker, and deploy them under guidance. - Code Quality: Refactor existing MVP research code into clean, modular, production-ready Python following team standards. - API Development: Write and optimize backend endpoints using FastAPI/Flask to seamlessly serve ML model inferences to our frontend client. - CI/CD & Monitoring: Manage Git workflows, maintain environment consistency, and monitor live model performance, API latencies, and logs. Qualification Required: - Experience: 2 years of professional software engineering experience, focused on backend development or data engineering. - Core Stack: Strong proficiency in Python and web framework development (FastAPI/Flask preferred). - Containerization: Practical, hands-on experience writing Dockerfiles and managing containerized applications. - Databases: Solid understanding of SQL (PostgreSQL) and NoSQL (MongoDB) for managing unstructured text data and user state. - AI/ML Familiarity: Basic experience interacting with PyTorch, Hugging Face pipelines, or commercial LLM APIs (OpenAI/Gemini). Understanding of passing data through an API to a model. Bonus Points (Nice-to-Haves): - Experience with frontend frameworks (React/Next.js) or building quick internal tools using Streamlit. - Basic knowledge of Agentic AI or Multi-Agent workflows (LangChain, LlamaIndex, AutoGen). - Familiarity with AdTech APIs (Google Ads, Meta Ads). If you join us, you will benefit from direct mentorship, hands-on exposure to PyTorch, LLMs, MLOps, and cloud infrastructure, and a clear path to a full-time role. In our startup environment, your work ships fast and makes an immediate impact. If you are ready to thrive in a fast-paced startup environment and contribute to building a deep-tech architecture from the ground up, please send your resume, salary expectations, references, and Gi